2,758 research outputs found
An Efficient Bit Plane X-OR Algorithm for Irreversible Image Steganography
The science of hiding secret information in another message is known as
Steganography; hence the presence of secret information is concealed. It is the
method of hiding cognitive content in same or another media to avoid
recognition by the intruders. This paper introduces new method wherein
irreversible steganography is used to hide an image in the same medium so that
the secret data is masked. The secret image is known as payload and the carrier
is known as cover image. X-OR operation is used amongst mid level bit planes of
carrier image and high level bit planes of data image to generate new low level
bit planes of the stego image. Recovery process includes the X-ORing of low
level bit planes and mid level bit planes of the stego image. Based on the
result of the recovery, subsequent data image is generated. A RGB color image
is used as carrier and the data image is a grayscale image of dimensions less
than or equal to the dimensions of the carrier image. The proposed method
greatly increases the embedding capacity without significantly decreasing the
PSNR value
Secret Image Sharing Using Grayscale Payload Decomposition and Irreversible Image Steganography
To provide an added security level most of the existing reversible as well as
irreversible image steganography schemes emphasize on encrypting the secret
image (payload) before embedding it to the cover image. The complexity of
encryption for a large payload where the embedding algorithm itself is complex
may adversely affect the steganographic system. Schemes that can induce same
level of distortion, as any standard encryption technique with lower
computational complexity, can improve the performance of stego systems. In this
paper we propose a secure secret image sharing scheme, which bears minimal
computational complexity. The proposed scheme, as a replacement for encryption,
diversifies the payload into different matrices which are embedded into carrier
image (cover image) using bit X-OR operation. A payload is a grayscale image
which is divided into frequency matrix, error matrix, and sign matrix. The
frequency matrix is scaled down using a mapping algorithm to produce Down
Scaled Frequency (DSF) matrix. The DSF matrix, error matrix, and sign matrix
are then embedded in different cover images using bit X-OR operation between
the bit planes of the matrices and respective cover images. Analysis of the
proposed scheme shows that it effectively camouflages the payload with minimum
computation time
A New Parallel Message-distribution Technique for Cost-based Steganography
This paper presents two novel approaches to increase performance bounds of
image steganography under the criteria of minimizing distortion. First, in
order to efficiently use the images' capacities, we propose using parallel
images in the embedding stage. The result is then used to prove sub-optimality
of the message distribution technique used by all cost based algorithms
including HUGO, S-UNIWARD, and HILL. Second, a new distribution approach is
presented to further improve the security of these algorithms. Experiments show
that this distribution method avoids embedding in smooth regions and thus
achieves a better performance, measured by state-of-the-art steganalysis, when
compared with the current used distribution
A reversible high embedding capacity data hiding technique for hiding secret data in images
As the multimedia and internet technologies are growing fast, the
transmission of digital media plays an important role in communication. The
various digital media like audio, video and images are being transferred
through internet. There are a lot of threats for the digital data that are
transferred through internet. Also, a number of security techniques have been
employed to protect the data that is transferred through internet. This paper
proposes a new technique for sending secret messages securely, using
steganographic technique. Since the proposed system uses multiple level of
security for data hiding, where the data is hidden in an image file and the
stego file is again concealed in another image. Previously, the secret message
is being encrypted with the encryption algorithm which ensures the achievement
of high security enabled data transfer through internet.Comment: IEEE Publication format, International Journal of Computer Science
and Information Security, IJCSIS, Vol. 7 No. 3, March 2010, USA. ISSN 1947
5500, http://sites.google.com/site/ijcsis
End-to-end Trained CNN Encode-Decoder Networks for Image Steganography
All the existing image steganography methods use manually crafted features to
hide binary payloads into cover images. This leads to small payload capacity
and image distortion. Here we propose a convolutional neural network based
encoder-decoder architecture for embedding of images as payload. To this end,
we make following three major contributions: (i) we propose a deep learning
based generic encoder-decoder architecture for image steganography; (ii) we
introduce a new loss function that ensures joint end-to-end training of
encoder-decoder networks; (iii) we perform extensive empirical evaluation of
proposed architecture on a range of challenging publicly available datasets
(MNIST, CIFAR10, PASCAL-VOC12, ImageNet, LFW) and report state-of-the-art
payload capacity at high PSNR and SSIM values
Combined Image Encryption and Steganography Algorithm in the Spatial Domain
In recent years, steganography has emerged as one of the main research areas
in information security. Least significant bit (LSB) steganography is one of
the fundamental and conventional spatial domain methods, which is capable of
hiding larger secret information in a cover image without noticeable visual
distortions. In this paper, a combined algorithm based on LSB steganography and
chaotic encryption is proposed. Experimental results show the feasibility of
the proposed method. In comparison with existing steganographic spatial domain
based algorithms, the suggested algorithm is shown to have some advantages over
existing ones, namely, larger key space and a higher level of security against
some existing attacks.Comment: 6 page
On the usefulness of information hiding techniques for wireless sensor networks security
A wireless sensor network (WSN) typically consists of base stations and a
large number of wireless sensors. The sensory data gathered from the whole
network at a certain time snapshot can be visualized as an image. As a result,
information hiding techniques can be applied to this "sensory data image".
Steganography refers to the technology of hiding data into digital media
without drawing any suspicion, while steganalysis is the art of detecting the
presence of steganography. This article provides a brief review of
steganography and steganalysis applications for wireless sensor networks
(WSNs). Then we show that the steganographic techniques are both related to
sensed data authentication in wireless sensor networks, and when considering
the attacker point of view, which has not yet been investigated in the
literature. Our simulation results show that the sink level is unable to detect
an attack carried out by the nsF5 algorithm on sensed data
An Improved Reversible Data Hiding in Encrypted Images using Parametric Binary Tree Labeling
This work proposes an improved reversible data hiding scheme in encrypted
images using parametric binary tree labeling(IPBTL-RDHEI), which takes
advantage of the spatial correlation in the entire original image but not in
small image blocks to reserve room for hiding data. Then the original image is
encrypted with an encryption key and the parametric binary tree is used to
label encrypted pixels into two different categories. Finally, one of the two
categories of encrypted pixels can embed secret information by bit replacement.
According to the experimental results, compared with several state-of-the-art
methods, the proposed IPBTL-RDHEI method achieves higher embedding rate and
outperforms the competitors. Due to the reversibility of IPBTL-RDHEI, the
original plaintext image and the secret information can be restored and
extracted losslessly and separately
High Capacity Lossless Data Hiding in JPEG Bitstream Based on General VLC Mapping
JPEG is the most popular image format, which is widely used in our daily
life. Therefore, reversible data hiding (RDH) for JPEG images is important.
Most of the RDH schemes for JPEG images will cause significant distortions and
large file size increments in the marked JPEG image. As a special case of RDH,
the lossless data hiding (LDH) technique can keep the visual quality of the
marked images no degradation. In this paper, a novel high capacity LDH scheme
is proposed. In the JPEG bitstream, not all the variable length codes (VLC) are
used to encode image data. By constructing the mapping between the used and
unused VLCs, the secret data can be embedded by replacing the used VLC with the
unused VLC. Different from the previous schemes, our mapping strategy allows
the lengths of unused and used VLCs in a mapping set to be unequal. We present
some basic insights into the construction of the mapping relationship.
Experimental results show that most of the JPEG images using the proposed
scheme obtain smaller file size increments than previous RDH schemes.
Furthermore, the proposed scheme can obtain high embedding capacity while
keeping the marked JPEG image with no distortion
Wavelet Based Authentication/Secret Transmission Through Image Resizing(WASTIR)
The paper is aimed for a wavelet based steganographic or watermarking
technique in frequency domain termed as WASTIR for secret message or image
transmission or image authentication. Number system conversion of the secret
image by changing radix form decimal to quaternary is the pre-processing of the
technique. Cover image scaling through inverse discrete wavelet transformation
with false Horizontal and vertical coefficients are embedded with quaternary
digits through hash function and a secret key. Experimental results are
computed and compared with the existing steganographic techniques like WTSIC,
Yuancheng Lis Method and Region-Based in terms of Mean Square Error (MSE), Peak
Signal to Noise Ratio (PSNR) and Image Fidelity (IF) which show better
performances in WASTIR.Comment: 10 Page Journal Paper, Sipi
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